How to include Heart Rate Variability (HRV) in your training plan

using objective and subjective data for flexible periodization

The aim of this blog is to answer the simple question above, i.e. how do you include HRV in your training plan?

There are plenty of articles on the basics of HRV and how it might be used to quantify recovery. However, there seems to be still a disconnect between the theory, and getting more practical in using the data effectively.

In particular, it is not uncommon for self-coached recreational athletes or beginners to use HRV as their guide to determine day-to-day load management without having a plan, which is in my opinion, a recipe for disaster.

Do you have a plan?

A common misconception is that HRV can guide our day-to-day training without a plan. This thinking is somewhat promoted by wearables that provide advice in the form of “your HRV is high, you must be primed to take so much Strain” or similar nonsense.

Let’s recap the basics: as we apply training stress to trigger certain adaptations. Measuring our body’s response to such stressors, as well as to all other forms of stress we are affected by (e.g. simply life happening, work stress, family, etc.), can provide objective feedback and help us make meaningful adjustments. The simpler adjustment is probably just being a little more honest with ourselves, and slowing down from time to time, especially when our body is already too stressed.

The example I’ve just highlighted is something we all understand quite well, higher stress as shown by lower HRV shows how it might be a good idea to take it easy and avoid excessive stress which might lead to overtraining or slower recoveries, hindering improvements in performance. So far so good, we might even get away with using HRV without a plan it seems. However: what do you do when it’s all good? Should you push it all the time because your HRV is within normal values, often shown in apps as a green light? Of course not.

The fact that your body is in a (physiologically speaking) normal state, is what you should aim for. Normal is good. However, this does not mean that every time HRV looks good you should go hard. Following the advice of a wearable does not lead to individualized training but to random training. No sensible training plan will tell you to go hard all the time. And following HRV (or feel or mood) to go hard until your HRV is suppressed or you feel terrible and are beyond saving, is clearly a poor approach.

You first need to have a plan, then you can make adjustments based on how you respond to such a plan. If your HRV is within your normal values, it should give you confidence that everything is going well and in general, you are coping well with your current training and lifestyle. Yet, if your training plan says you are due for a rest day, take it. If you are due for a low-intensity workout, do it.

HRV and physiological measurements are tools for awareness, which allow you to understand how you respond to a particular plan, not to replace your plan entirely.

Now that we’ve cleared that up, we should ask ourselves another question: if we went through the trouble to get a good plan, why would we want to consider adding HRV?

Your HRV is within your normal range and your subjective scores are trending positively: PROCEED AS PLANNED. Some apps are just better than others.

Flexible periodization

In my opinion, there are a few reasons to use HRV, starting with improving our awareness (something I discuss below), but mostly, in the context of training, it’s about flexible periodization.

Standard periodization including e.g. 2-3 weeks of high load followed by 1 week of lower load does not consider the very large inter and intra-individual variability in response to a fixed program. In terms of inter-individual differences, some people might be able to train for more weeks without extra recovery, others might need it more frequently, some might have a more demanding job or family duties, etc. In terms of intra-individual differences, we also have large differences: there might be periods in which the same person is able to absorb more load and periods in which they are not, because of e.g. additional stressors (psychological or physical, doesn’t really matter, our capacity remains limited).

If we agree that a standard, fixed periodization lacks individualization, then we also understand that a flexible periodization, where periods of higher or lower load can be modulated based on the necessities of the moment, might be preferable.

My approach

My approach to training has evolved a lot with the work I’ve been doing with HRV4Training as well as the injuries I have experienced, becoming more and more flexible over time. I normally design a very generic and flexible plan and then adjust it based on objective (e.g. HRV) and subjective (e.g. feel) data. If you are self-coached, you can easily do the same. If you do have a coach, there is probably already a process in place for implementing changes when the response is not the one you were hoping for, and this process can be extended using both subjective and objective data.

The way I plan is the following: I first break down the year or next several months based on the races I’m targeting and split the plan into macro periodization blocks, e.g. more polarized or pyramidal depending on the time of the year and demands of the event. Then, within each macroblock, I include the main sessions that I’d like to do based on the adaptations I’m seeking (e.g. short or long intervals, long runs at marathon pace, etc.).

Then, as the days go by, I let my body decide when I can do those specific sessions, and fill the remaining days with as much easy running as I can sustain, without compromising the key sessions. There is no fixed day for a workout or long run, but there are always 3 easy days between sessions, and there is always one day off per week. This structure, the plan, is the key starting point.

Using subjective (feel) and objective (HRV) data

Objective and subjective data are often antagonized in rather useless arguments. However, in my experience, they can largely benefit from each other. For example:

1. we can fine-tune feel using data: we can get better at understanding our body and using subjective feel for guidance, by using data. Our awareness will improve as we start paying more attention and use e.g. HRV as an objective marker of physiological stress. The same applies to using heart rate during exercise, something I discussed more extensively here. I am sure I can do most of my training without any data these days, but to get here, I used data as feedback. Before, I had a plan and structure, but I had no idea I was always training too hard and as a result, I made no progress for many years. Objective data made me slow down and solved the problem, leading to great improvements in performance. As beginners, we simply have no idea what it means to run easy, feel is not an innate ability, despite what your favorite self-help guru might say. Objective data can help. As simple as that.

2. we can use data to backup feel or as early warnings: when feel and HRV agree, you have fewer doubts about the action plan. If I don’t feel good and the data shows a suppression in HRV, I know it’s not a good day for a hard session (again, feel is complex, and confirmation from objective data can be helpful, even if you have good self-awareness). Similarly, if both HRV and feel show positive trends, I gain confidence that I am responding well to my training plan. When HRV and feel do not agree, it is an even more useful exercise in self-awareness and self-reflection. My recommendation in these cases is not to overthink an acute suppression if you feel good, but to pay attention when the suppression in HRV is lasting more than one day: in that case, your body is trying to tell you something. Depending on your level, adjusting the plan has different meanings: for a beginner, a day off might be a good idea. For a more experienced athlete, normally reducing intensity is sufficient, as intensity is the main driver of disruptions in autonomic activity (as I discuss here).

3. we can manage non-training-related stress: we all experience non-training-related stressors (work, travel, sickness, etc.). All of these stressors have great implications in terms of what we can do in training and can often be better managed with some objective feedback.

Using HRV should not be about blind guidance, or trusting the data over ourselves, but it should be helping us fine-tune our self-awareness, or understand when something is off, sometimes accepting that we might need to change plans, even for longer than we’d like, to avoid chronic negative responses (e.g. burnout, overtraining, etc.).

Taking a minute to pause and assess how you are feeling using a short questionnaire can go a long way.

What about training harder?

When I talk about HRV, I often focus on preventing the negative, as Jason Koop puts it in his framework. During my conversation with Jason’s group, I was asked if we could also use a higher HRV to prompt a harder session or block.

While I think that stability and gradually increasing HRV are indicators of long-term positive endurance adaptations, acute positive changes in HRV likely cannot be used to prompt a big training stimulus as outliers of this type (i.e. a very high HRV on a given day) might even be associated with strong stressors (an overly active recovery system, as opposed to a very recovered one). This is another reason why I believe in the importance of providing a normal range and moving away from “higher is better” interpretations common in wearables.

This being said, I’ve been thinking about this some more, and I think there might be room for flexibility depending on the plan. For example, often, our plan is already packed with as many sessions as we can possibly handle, and therefore, even if our response was positive, it would be difficult to make changes (I cannot think of a single time that I was able to add more workouts to my training, instead of having to remove some). Maybe we can add an extra rep, or a slightly longer run, but it would be about minimal changes, more than adding an additional workout. Additionally, we should also consider that in certain sports (e.g. running), muscular load and injury risk can increase by adding more workouts, and a positive HRV is typically not indicative of muscular soreness or muscular issues. However, if your plan is particularly conservative, maybe when working with a novice athlete, then we might be able to add load in periods in which HRV is trending well, not acutely, but in terms of baseline changes with respect to the normal range. These are my thoughts right now on the topic, not something derived from literature, which is rather scarce.

Research vs real-life

Hopefully, the sections above gave you some useful pointers on how to use HRV in the context of your training plan and together with subjective feel. Another point I’d like to address derives from many conversations I had where athletes would look at a given study, and then try to apply the exact same protocol to their training. While some of these protocols are well thought out, we need to remember that research and real life can be very different. In the example below, I’ll show you a case in which it makes little sense to follow research protocols. We need to be flexible in how we use the data.

State-of-the-art research relies on baseline changes with respect to the normal range, to determine if training should be modified (e.g. reduced in intensity). This is an evolution of earlier research that would look at daily changes, and implement changes when a suppression in HRV was present.

The newer approach based on baseline changes does make sense: we are not too reactive anymore, and only implement changes when a more meaningful negative response is present (it will always take a few days of suppressions for the baseline to go below the normal range).

While in the context of training responses, this might be a good approach, real life is different, and other stressors might need to be treated differently. On February 1st I was sick, my baseline cannot be suppressed just yet, despite a very low daily HRV, and HRV-guided training studies would recommend I train hard, if that was my plan.

Note that the opposite is also true: after large stressors (Feb 1st-5th), the baseline gets suppressed when you are actually starting to feel better. As I am back within the normal range on the 6th and 7th of February, the baseline prompts a reduction in training intensity. This baseline-driven approach often creates a mismatch between feel and HRV changes, as baseline changes are delayed by definition.

This is important because, in my opinion, baseline changes might be better for retrospective analysis (they remove some of the noise), but not necessarily for day-to-day guidance. This is the approach used by Garmin's HRV analysis (HRV status), which is better than some alternatives (at least it includes a normal range) but only provides an overview of baseline trends, often missing key, daily changes.

This is all to say that using HRV is not about employing simple rules and not thinking about what we are doing, quite the contrary. Research allows us to investigate in more systematic ways different approaches, but real life is different, and our approach should likely be different too.

Wrap-up

When using HRV, we need to start with a plan, a plan that includes adequate recovery post-hard sessions, depending on the level of the athlete, their recovery abilities, and other commitments.

We can then use a combination of feel and HRV to determine individual responses and make adjustments to our plan. Note that this is very different from relying on readiness or recovery scores, which combine various parameters (sleep, activity, etc.), but never ask you how you feel.

HRV within normal values should give you confidence that everything is going well and in general, you are coping well with your current training and lifestyle. Yet, if your training plan says you are due for a rest day, take it. If you are due for a low-intensity workout, do it.

If you have been using HRV4Training, you should see some of these principles reflected in how we designed our platform: the importance of interpreting the data with respect to your normal range, combining objective data and subjective feel via the questionnaire, and the advice recommending to proceed as planned, when things are going well.

I hope this was informative, and thank you for reading!

Marco holds a PhD cum laude in applied machine learning, a M.Sc. cum laude in computer science engineering, and a M.Sc. cum laude in human movement sciences and high-performance coaching.

He has published more than 50 papers and patents at the intersection between physiology, health, technology, and human performance.

He is co-founder of HRV4Training, advisor at Oura, guest lecturer at VU Amsterdam, and editor for IEEE Pervasive Computing Magazine. He loves running.

Twitter: @altini_marco

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